suppressPackageStartupMessages({
library("here")
library("tidyverse")
library("MplusAutomation")
library("gt")
library("glue")
library("kableExtra")
library("misty")
library("lavaan")
library("AICcmodavg")
library("nonnest2")
library("DiagrammeR")
library("lavaan")
library("tidyLPA")
library("semTools")
library("brms")
library("MBESS")
library("ufs")
library("robmed")
library("careless")
library("mice")
library("psych")
library("BayesFactor")
library("effectsize")
library("tidybayes")
library("emmeans")
library("bayesplot")
library("patchwork")
library("bmlm")
})
options("max.print" = .Machine$integer.max)
set.seed(1234)
options(mc.cores = 4)
bayesplot_theme_set()
source(here::here("src", "functions", "funs_add_neoffi60_subscales.R"))
source(here::here("src", "functions", "funs_correct_iesr_scores.R"))
source(here::here("src", "functions", "funs_plot_job_qualification.R"))
source(here::here("src", "functions", "funs_generate_all_items_df.R"))
scale_this <- function(x) as.vector(scale(x))
sum_coding <- function(x, lvls = levels(x)) {
# codes the first category with -1
nlvls <- length(lvls)
stopifnot(nlvls > 1)
cont <- diag(nlvls)[, -nlvls, drop = FALSE]
cont[nlvls, ] <- -1
cont <- cont[c(nlvls, 1:(nlvls - 1)), , drop = FALSE]
colnames(cont) <- lvls[-1]
x <- factor(x, levels = lvls)
contrasts(x) <- cont
x
}
all_items <- rio::import(
here::here("data", "final", "rescue_workers_data.csv")
)
iesr_ts | trunc(lb = 0) ~ is_rescue_worker + (1 | commeetee),
m0 <- brm(
bf(iesr_ts ~ is_rescue_worker),
family = hurdle_gamma(),
data = all_items,
backend = "cmdstanr"
# algorithm = "meanfield"
)
## Start sampling
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: Exception: gamma_lpdf: Inverse scale parameter is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 16, column 6 to column 66) (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 80, column 6 to column 67)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: Exception: gamma_lpdf: Inverse scale parameter is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 16, column 6 to column 66) (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 80, column 6 to column 67)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: Exception: gamma_lpdf: Inverse scale parameter is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 16, column 6 to column 66) (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 80, column 6 to column 67)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: gamma_lpdf: Random variable is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: gamma_lpdf: Random variable is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: Exception: gamma_lpdf: Inverse scale parameter is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 16, column 6 to column 66) (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 80, column 6 to column 67)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: gamma_lpdf: Random variable is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136da8eaa.stan', line 69, column 2 to column 43)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(m0)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
summary(m0)
## Family: hurdle_gamma
## Links: mu = log; shape = identity; hu = identity
## Formula: iesr_ts ~ is_rescue_worker
## Data: all_items (Number of observations: 1068)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept 2.67 0.06 2.55 2.80 1.00 3465 2919
## is_rescue_workerSi 0.29 0.07 0.13 0.42 1.00 3788 3059
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## shape 1.40 0.06 1.29 1.52 1.00 3710 3184
## hu 0.17 0.01 0.15 0.19 1.00 4640 2881
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
me <- conditional_effects(
m0, "is_rescue_worker"
)
plot(me, points = FALSE)
BFt <- BayesFactor::ttestBF(
all_items$ies_ts[all_items$is_rescue_worker == "Si"],
all_items$ies_ts[all_items$is_rescue_worker == "No"],
paired = FALSE
)
effectsize(BFt)
Supported families are: ‘acat’, ‘asym_laplace’, ‘bernoulli’, ‘beta’, ‘beta_binomial’, ‘binomial’, ‘categorical’, ‘com_poisson’, ‘cox’, ‘cratio’, ‘cumulative’, ‘custom’, ‘dirichlet’, ‘dirichlet2’, ‘discrete_weibull’, ‘exgaussian’, ‘exponential’, ‘frechet’, ‘gamma’, ‘gaussian’, ‘gen_extreme_value’, ‘geometric’, ‘hurdle_cumulative’, ‘hurdle_gamma’, ‘hurdle_lognormal’, ‘hurdle_negbinomial’, ‘hurdle_poisson’, ‘info’, ‘inverse.gaussian’, ‘logistic_normal’, ‘lognormal’, ‘multinomial’, ‘negbinomial’, ‘negbinomial2’, ‘poisson’, ‘shifted_lognormal’, ‘skew_normal’, ‘sratio’, ‘student’, ‘von_mises’, ‘weibull’, ‘wiener’, ‘zero_inflated_asym_laplace’, ‘zero_inflated_beta’, ‘zero_inflated_beta_binomial’, ‘zero_inflated_binomial’, ‘zero_inflated_negbinomial’, ‘zero_inflated_poisson’, ‘zero_one_inflated_beta’
The sk, ch, mi sub-scales are coded so that high values indicate high self-compassion levels. The sj, is, oi sub-scales are coded so that high values indicate low self-compassion levels.
The ts_sc score has been computed by reversing the coding of the items of the sj, is, oi sub-scales (so that they indicate the absence of self-judgment, absence of isolation, absence of over-identification).
scs_subscales <- with(all_items, data.frame(sk, ch, mi, sj, is, oi, scs_ts))
cor(scs_subscales) |> round(2)
## sk ch mi sj is oi scs_ts
## sk 1.00 0.52 0.58 -0.39 -0.28 -0.24 0.71
## ch 0.52 1.00 0.49 -0.01 -0.03 -0.04 0.45
## mi 0.58 0.49 1.00 -0.19 -0.33 -0.35 0.66
## sj -0.39 -0.01 -0.19 1.00 0.67 0.66 -0.75
## is -0.28 -0.03 -0.33 0.67 1.00 0.80 -0.78
## oi -0.24 -0.04 -0.35 0.66 0.80 1.00 -0.78
## scs_ts 0.71 0.45 0.66 -0.75 -0.78 -0.78 1.00
In the COPE scale only two factors are identified.
all_items$pos_reinterpretation <- with(all_items, cope_1 + cope_29 + cope_38 + cope_59)
all_items$mental_disengagement <- with(all_items, cope_2 + cope_16 + cope_31 + cope_43)
all_items$venting <- with(all_items, cope_3 + cope_17 + cope_28 + cope_46)
all_items$seeking_instrumental_support <- with(all_items, cope_4 + cope_14 + cope_30 + cope_45)
all_items$active_coping <- with(all_items, cope_5 + cope_25 + cope_47 + cope_58)
all_items$denial <- with(all_items, cope_6 + cope_27 + cope_40 + cope_57)
all_items$religion <- with(all_items, cope_7 + cope_18 + cope_48 + cope_60)
all_items$humor <- with(all_items, cope_8 + cope_20 + cope_36 + cope_50)
all_items$behavioral_disengagement <- with(all_items, cope_9 + cope_24 + cope_37 + cope_51)
all_items$restraint <- with(all_items, cope_10 + cope_22 + cope_41 + cope_49)
all_items$seeking_emotional_support <- with(all_items, cope_11 + cope_23 + cope_34 + cope_52)
all_items$substance_use <- with(all_items, cope_12 + cope_26 + cope_35 + cope_53)
all_items$acceptance <- with(all_items, cope_13 + cope_21 + cope_44 + cope_54)
all_items$suppr_competing_activities <- with(all_items, cope_15 + cope_33 + cope_42 + cope_55)
all_items$planning <- with(all_items, cope_19 + cope_32 + cope_39 + cope_56)
Create COPE sub-scales scores using all items – note that SEM analyses suggest to drop some of the items.
all_items$active_coping <- with(
all_items, pos_reinterpretation + active_coping +
suppr_competing_activities + planning + restraint +
seeking_instrumental_support + acceptance
)
all_items$avoidance_coping <- with(
all_items, mental_disengagement + denial + humor +
behavioral_disengagement + substance_use + religion
)
all_items$soc_emo_coping <- with(
all_items, seeking_instrumental_support +
seeking_emotional_support + venting
)
plot(density(all_items$scs_ts))
fit_1 <- brm(
bf(
scs_ts ~ is_rescue_worker,
sigma ~ is_rescue_worker
),
family = student(),
backend = "cmdstanr",
data = all_items
)
## Start sampling
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: student_t_lpdf: Scale parameter[1] is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce134d6708cf.stan', line 88, column 4 to column 48)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(fit_1)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
me <- conditional_effects(
fit_1, "is_rescue_worker"
)
plot(me, points = FALSE)
summary(fit_1)
## Family: student
## Links: mu = identity; sigma = log; nu = identity
## Formula: scs_ts ~ is_rescue_worker
## sigma ~ is_rescue_worker
## Data: all_items (Number of observations: 1068)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS
## Intercept 74.11 1.03 72.12 76.10 1.00 3819
## sigma_Intercept 2.89 0.04 2.80 2.97 1.00 4042
## is_rescue_workerSi 7.46 1.21 5.09 9.79 1.00 4289
## sigma_is_rescue_workerSi -0.13 0.05 -0.22 -0.03 1.00 4265
## Tail_ESS
## Intercept 2910
## sigma_Intercept 3094
## is_rescue_workerSi 3199
## sigma_is_rescue_workerSi 3213
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## nu 38.81 15.88 17.01 76.86 1.00 3827 3206
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
BFt <- BayesFactor::ttestBF(
all_items$scs_ts[all_items$is_rescue_worker == "Si"],
all_items$scs_ts[all_items$is_rescue_worker == "No"],
paired = FALSE
)
effectsize(BFt)
rw_df <- all_items |>
dplyr::filter(is_rescue_worker == "Si")
rw_df <- rw_df %>%
mutate(job_qualification = case_when(
job_qualification == "non_rescue_worker" ~ "team_member",
TRUE ~ job_qualification))
lpa_scales <- c(
"is_rescue_worker",
"neuroticism", "extraversion", "openness", "agreeableness", "conscientiousness",
"active_coping", "avoidance_coping", "soc_emo_coping",
"iesr_ts",
# "avoiding", "intrusivity", "hyperarousal",
# "sk", "ch", "mi", "sj", "is", "oi",
# "pos_sc",
# "neg_sc",
# "ts_sc",
"mpss_tot"
# "ptgi_total_score"
# "relating_to_others",
# "new_possibilities",
# "personal_strength",
# "appreciation_of_life",
# "spirituality"
)
lpa_rw_df <- subset(rw_df, select=lpa_scales)
# lpa_rw_df <- subset(all_items, select=lpa_scales) |>
# dplyr::filter(is_rescue_worker == "Si")
lpa_rw_df$is_rescue_worker <- NULL
lpa_rw_df <- lpa_rw_df |>
dplyr::rename(
mpss = mpss_tot,
iesr = iesr_ts
)
head(lpa_rw_df)
lpa_rw_df %>%
scale() %>%
estimate_profiles(1:10,
variances = c("equal", "varying"),
covariances = c("zero", "varying")
#package = "MplusAutomation"
)
## tidyLPA analysis using mclust:
##
## Model Classes AIC BIC Entropy prob_min prob_max n_min n_max BLRT_p
## 1 1 21342.45 21434.88 1.00 1.00 1.00 1.00 1.00
## 1 2 20740.67 20883.93 0.71 0.88 0.94 0.36 0.64 0.01
## 1 3 20460.08 20654.18 0.75 0.81 0.93 0.19 0.56 0.01
## 1 4 20335.36 20580.29 0.73 0.84 0.86 0.11 0.36 0.01
## 1 5 20199.94 20495.71 0.73 0.79 0.87 0.08 0.32 0.01
## 1 6 20148.07 20494.68 0.73 0.73 0.88 0.07 0.36 0.01
## 1 7 20080.74 20478.18 0.76 0.72 0.88 0.05 0.37 0.01
## 1 8 20014.89 20463.17 0.77 0.71 0.90 0.03 0.36 0.01
## 1 9 19965.51 20464.63 0.76 0.76 0.88 0.04 0.27 0.01
## 1 10 19948.33 20498.28 0.75 0.69 0.92 0.02 0.22 0.01
## 6 1 19883.12 20183.51 1.00 1.00 1.00 1.00 1.00
## 6 2 19509.40 20114.80 0.70 0.89 0.94 0.44 0.56 0.01
## 6 3 19416.00 20326.42 0.73 0.88 0.89 0.23 0.39 0.01
## 6 4 19366.48 20581.91 0.80 0.88 0.90 0.09 0.40 0.01
## 6 5 19360.48 20880.92 0.79 0.83 0.92 0.11 0.37 0.09
## 6 6 19313.54 21138.99 0.82 0.84 0.98 0.07 0.29 0.01
## 6 7 19374.46 21504.93 0.82 0.83 0.98 0.07 0.28 0.96
## 6 8 19285.55 21721.03 0.85 0.83 0.99 0.07 0.22 0.01
## 6 9 19275.58 22016.07 0.87 0.88 0.97 0.07 0.18 0.15
## 6 10 19342.60 22388.10 0.88 0.87 0.98 0.06 0.14 1.00
lpa_rw_df %>%
scale() %>%
estimate_profiles(1:10,
variances = c("equal", "varying"),
covariances = c("zero", "varying")
# package = "MplusAutomation"
) %>%
compare_solutions(statistics = c("AIC", "BIC"))
## Compare tidyLPA solutions:
##
## Model Classes AIC BIC
## 1 1 21342.450 21434.878
## 1 2 20740.667 20883.931
## 1 3 20460.078 20654.177
## 1 4 20335.356 20580.291
## 1 5 20199.937 20495.707
## 1 6 20148.075 20494.680
## 1 7 20080.739 20478.180
## 1 8 20014.893 20463.169
## 1 9 19965.515 20464.627
## 1 10 19948.330 20498.277
## 6 1 19883.119 20183.510
## 6 2 19509.400 20114.804
## 6 3 19416.002 20326.419
## 6 4 19366.479 20581.908
## 6 5 19360.483 20880.925
## 6 6 19313.536 21138.991
## 6 7 19374.457 21504.925
## 6 8 19285.553 21721.034
## 6 9 19275.581 22016.074
## 6 10 19342.597 22388.103
##
## Best model according to AIC is Model 6 with 9 classes.
## Best model according to BIC is Model 6 with 2 classes.
##
## An analytic hierarchy process, based on the fit indices AIC, AWE, BIC, CLC, and KIC (Akogul & Erisoglu, 2017), suggests the best solution is Model 6 with 2 classes.
m2 <- lpa_rw_df %>%
scale() %>%
estimate_profiles(2,
variances = "varying",
covariances = "varying",
package = "MplusAutomation"
)
m2_plot <- lpa_rw_df %>%
scale() %>%
estimate_profiles(2,
variances = "varying",
covariances = "varying",
package = "MplusAutomation"
) %>%
plot_profiles(add_line = TRUE, rawdata= FALSE, bw = FALSE)
Profile 2: dysfunctional Profile 1: adaptive
get_estimates(m2)
out <- get_data(m2)
lpa_rw_df$lpa_class <- out$Class
table(
lpa_rw_df$lpa_class
)
##
## 1 2
## 408 343
table(
lpa_rw_df$lpa_class, rw_df$job_qualification
)
##
## driver team_leader team_member
## 1 96 160 152
## 2 59 139 145
lpa_rw_df$class <- factor(lpa_rw_df$lpa_class)
summary(lpa_rw_df$class)
## 1 2
## 408 343
rw_df$class <- lpa_rw_df$class
rw_df$profile <- lpa_rw_df$class
rw_df$profile <- ifelse(
rw_df$profile == "2", "maladaptive", "adaptive"
)
rw_df$profile <- factor(rw_df$profile)
# Reorder the levels of the 'profile' factor
rw_df$profile <- factor(rw_df$profile, levels = c("maladaptive", "adaptive"))
m1 <- brm(
bf(scs_ts ~ profile),
family = skew_normal(),
data = rw_df,
init = 0.1,
backend = "cmdstanr",
adapt_delta = 0.9
)
## Start sampling
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1350a8ea60.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(m1)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
summary(m1)
## Family: skew_normal
## Links: mu = identity; sigma = identity; alpha = identity
## Formula: scs_ts ~ profile
## Data: rw_df (Number of observations: 751)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept 74.47 0.83 72.78 76.08 1.00 3366 2848
## profileadaptive 12.78 1.14 10.57 15.01 1.00 3158 2539
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 14.89 0.40 14.17 15.73 1.00 2896 2576
## alpha -0.65 0.60 -1.51 0.62 1.00 1612 2971
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
me <- conditional_effects(
m1, "profile"
)
plot(me, points = FALSE)
BFt <- BayesFactor::ttestBF(
rw_df$scs_ts[rw_df$class == 1],
rw_df$scs_ts[rw_df$class == 2],
paired = FALSE
)
effectsize(BFt, type = "d")
m1 %>%
emmeans( ~ profile) %>%
gather_emmeans_draws() %>%
ggplot(aes(x = profile, y = .value)) +
geom_eye() +
stat_summary(aes(group = NA), fun.y = mean, geom = "line") +
# facet_grid(~ wool) +
# theme_light()
labs(x = "LPA Class", y = "SCS Score", title = "Rescue Workers") +
papaja::theme_apa() +
annotate("text", x = 1, y = 83, label = "Bayesian Cohen's d = 0.89\n 95% CI [0.73, 1.04]")
## Warning: 'geom_eye' is deprecated.
## Use 'stat_eye' instead.
## See help("Deprecated") and help("tidybayes-deprecated").
## Warning: The `fun.y` argument of `stat_summary()` is deprecated as of ggplot2 3.3.0.
## ℹ Please use the `fun` argument instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
names(all_items)
## [1] "ies_1" "ies_2"
## [3] "ies_3" "ies_4"
## [5] "ies_5" "ies_6"
## [7] "ies_7" "ies_8"
## [9] "ies_9" "ies_10"
## [11] "ies_11" "ies_12"
## [13] "ies_13" "ies_14"
## [15] "ies_15" "ies_16"
## [17] "ies_17" "ies_18"
## [19] "ies_19" "ies_20"
## [21] "ies_21" "ies_22"
## [23] "id" "group"
## [25] "avoiding" "intrusivity"
## [27] "hyperarousal" "ies_ts"
## [29] "grp.x" "grp.y"
## [31] "neoffi_1" "neoffi_2"
## [33] "neoffi_3" "neoffi_4"
## [35] "neoffi_5" "neoffi_6"
## [37] "neoffi_7" "neoffi_8"
## [39] "neoffi_9" "neoffi_10"
## [41] "neoffi_11" "neoffi_12"
## [43] "neoffi_13" "neoffi_14"
## [45] "neoffi_15" "neoffi_16"
## [47] "neoffi_17" "neoffi_18"
## [49] "neoffi_19" "neoffi_20"
## [51] "neoffi_21" "neoffi_22"
## [53] "neoffi_23" "neoffi_24"
## [55] "neoffi_25" "neoffi_26"
## [57] "neoffi_27" "neoffi_28"
## [59] "neoffi_29" "neoffi_30"
## [61] "neoffi_31" "neoffi_32"
## [63] "neoffi_33" "neoffi_34"
## [65] "neoffi_35" "neoffi_36"
## [67] "neoffi_37" "neoffi_38"
## [69] "neoffi_39" "neoffi_40"
## [71] "neoffi_41" "neoffi_42"
## [73] "neoffi_43" "neoffi_44"
## [75] "neoffi_45" "neoffi_46"
## [77] "neoffi_47" "neoffi_48"
## [79] "neoffi_49" "neoffi_50"
## [81] "neoffi_51" "neoffi_52"
## [83] "neoffi_53" "neoffi_54"
## [85] "neoffi_55" "neoffi_56"
## [87] "neoffi_57" "neoffi_58"
## [89] "neoffi_59" "neoffi_60"
## [91] "cope_1" "cope_2"
## [93] "cope_3" "cope_4"
## [95] "cope_5" "cope_6"
## [97] "cope_7" "cope_8"
## [99] "cope_9" "cope_10"
## [101] "cope_11" "cope_12"
## [103] "cope_13" "cope_14"
## [105] "cope_15" "cope_16"
## [107] "cope_17" "cope_18"
## [109] "cope_19" "cope_20"
## [111] "cope_21" "cope_22"
## [113] "cope_23" "cope_24"
## [115] "cope_25" "cope_26"
## [117] "cope_27" "cope_28"
## [119] "cope_29" "cope_30"
## [121] "cope_31" "cope_32"
## [123] "cope_33" "cope_34"
## [125] "cope_35" "cope_36"
## [127] "cope_37" "cope_38"
## [129] "cope_39" "cope_40"
## [131] "cope_41" "cope_42"
## [133] "cope_43" "cope_44"
## [135] "cope_45" "cope_46"
## [137] "cope_47" "cope_48"
## [139] "cope_49" "cope_50"
## [141] "cope_51" "cope_52"
## [143] "cope_53" "cope_54"
## [145] "cope_55" "cope_56"
## [147] "cope_57" "cope_58"
## [149] "cope_59" "cope_60"
## [151] "ptgi_1" "ptgi_2"
## [153] "ptgi_3" "ptgi_4"
## [155] "ptgi_5" "ptgi_6"
## [157] "ptgi_7" "ptgi_8"
## [159] "ptgi_9" "ptgi_10"
## [161] "ptgi_11" "ptgi_12"
## [163] "ptgi_13" "ptgi_14"
## [165] "ptgi_15" "ptgi_16"
## [167] "ptgi_17" "ptgi_18"
## [169] "ptgi_19" "ptgi_20"
## [171] "ptgi_21" "scs_1"
## [173] "scs_2" "scs_3"
## [175] "scs_4" "scs_5"
## [177] "scs_6" "scs_7"
## [179] "scs_8" "scs_9"
## [181] "scs_10" "scs_11"
## [183] "scs_12" "scs_13"
## [185] "scs_14" "scs_15"
## [187] "scs_16" "scs_17"
## [189] "scs_18" "scs_19"
## [191] "scs_20" "scs_21"
## [193] "scs_22" "scs_23"
## [195] "scs_24" "scs_25"
## [197] "scs_26" "mspss_1"
## [199] "mspss_2" "mspss_3"
## [201] "mspss_4" "mspss_5"
## [203] "mspss_6" "mspss_7"
## [205] "mspss_8" "mspss_9"
## [207] "mspss_10" "mspss_11"
## [209] "mspss_12" "date"
## [211] "gender" "age"
## [213] "education" "employment"
## [215] "is_rescue_worker" "red_cross_commeetee_location"
## [217] "rescue_worker_qualification" "last_training"
## [219] "rate_of_activity" "job_qualification"
## [221] "is_job_qualification_invariant" "is_team_invariant"
## [223] "is_married" "FLAG_1"
## [225] "neuroticism" "extraversion"
## [227] "openness" "agreeableness"
## [229] "conscientiousness" "social_support"
## [231] "avoiding_strategies" "positive_attitude"
## [233] "problem_orientation" "transcendent_orientation"
## [235] "cope_total_score" "relating_to_others"
## [237] "new_possibilities" "personal_strength"
## [239] "appreciation_of_life" "spirituality"
## [241] "ptgi_total_score" "ies_total_score"
## [243] "self_kindness" "self_judgment"
## [245] "common_humanity" "isolation"
## [247] "mindfulness" "over_identification"
## [249] "neg_self_compassion" "pos_self_compassion"
## [251] "scs_ts" "sk"
## [253] "ch" "mi"
## [255] "sj" "is"
## [257] "oi" "family"
## [259] "friends" "significant_other"
## [261] "mpss_tot" "iesr_ts"
## [263] "negative_affect" "self_reproach"
## [265] "positive_affect" "sociability"
## [267] "activity" "aesthetic_interests"
## [269] "intellectual_interests" "unconventionality"
## [271] "nonantagonistic_orientation" "prosocial_orientation"
## [273] "orderliness" "goal_striving"
## [275] "dependability" "rate_of_activity_num"
## [277] "last_training_num" "education_num"
## [279] "y" "commeetee_location"
## [281] "commeetee" "pos_reinterpretation"
## [283] "mental_disengagement" "venting"
## [285] "seeking_instrumental_support" "active_coping"
## [287] "denial" "religion"
## [289] "humor" "behavioral_disengagement"
## [291] "restraint" "seeking_emotional_support"
## [293] "substance_use" "acceptance"
## [295] "suppr_competing_activities" "planning"
## [297] "avoidance_coping" "soc_emo_coping"
m2 <- brm(
bf(sj ~ profile),
data = rw_df,
family = student,
backend = "cmdstanr",
adapt_delta = 0.99
)
## Start sampling
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370aa230.stan', line 75, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370aa230.stan', line 75, column 4 to column 48)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370aa230.stan', line 75, column 4 to column 48)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: gamma_lpdf: Random variable is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370aa230.stan', line 67, column 2 to column 66)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370aa230.stan', line 75, column 4 to column 48)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370aa230.stan', line 75, column 4 to column 48)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370aa230.stan', line 75, column 4 to column 48)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: gamma_lpdf: Random variable is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370aa230.stan', line 67, column 2 to column 66)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(m2)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
loo_m2 <- loo(m2)
plot(loo_m2)
summary(m2)
## Family: student
## Links: mu = identity; sigma = identity; nu = identity
## Formula: sj ~ profile
## Data: rw_df (Number of observations: 751)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept 17.06 0.24 16.58 17.53 1.00 3359 2280
## profileadaptive -3.65 0.33 -4.32 -3.00 1.00 3275 2392
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 4.26 0.12 4.05 4.49 1.00 3027 2273
## nu 46.60 17.34 21.71 87.88 1.00 3183 2933
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
me <- conditional_effects(
m2, "profile"
)
plot(me, points = FALSE)
emmeans(m2, specs = pairwise ~ profile)
## $emmeans
## profile emmean lower.HPD upper.HPD
## maladaptive 17.1 16.6 17.5
## adaptive 13.4 13.0 13.8
##
## Point estimate displayed: median
## HPD interval probability: 0.95
##
## $contrasts
## contrast estimate lower.HPD upper.HPD
## maladaptive - adaptive 3.65 3.02 4.34
##
## Point estimate displayed: median
## HPD interval probability: 0.95
BFt <- BayesFactor::ttestBF(
rw_df$sj[rw_df$profile == "adaptive"],
rw_df$sj[rw_df$profile == "maladaptive"],
paired = FALSE
)
effectsize(BFt)
p2 <- m2 %>%
emmeans( ~ profile) %>%
gather_emmeans_draws() %>%
ggplot(aes(x = profile, y = .value)) +
geom_eye() +
stat_summary(aes(group = NA), fun.y = mean, geom = "line") +
# facet_grid(~ wool) +
# theme_light()
scale_x_discrete(labels=c('Low Resilience', 'High Resilience')) +
labs(x = "LPA Class", y = "SCS Self-Judgment", title = "A") +
papaja::theme_apa() +
annotate("text", x = 1, y = 14.5, label = "Bayesian Cohen's d = 0.82\n 95% CI [0.67, 0.97]")
## Warning: 'geom_eye' is deprecated.
## Use 'stat_eye' instead.
## See help("Deprecated") and help("tidybayes-deprecated").
p2
m3 <- brm(
bf(is ~ profile),
family = skew_normal(),
data = rw_df,
backend = "cmdstanr",
adapt_delta = 0.95
)
## Start sampling
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1365576876.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(m3)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
loo_m3 <- loo(m3)
plot(loo_m3)
summary(m3)
## Family: skew_normal
## Links: mu = identity; sigma = identity; alpha = identity
## Formula: is ~ profile
## Data: rw_df (Number of observations: 751)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept 12.31 0.24 11.82 12.76 1.00 2271 2283
## profileadaptive -3.41 0.33 -4.06 -2.77 1.00 2389 2296
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 4.06 0.12 3.83 4.30 1.00 2806 2480
## alpha 2.25 0.66 1.00 3.58 1.00 2198 2191
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
me <- conditional_effects(
m3, "profile"
)
plot(me, points = FALSE)
emmeans(m3, specs = pairwise ~ profile)
## $emmeans
## profile emmean lower.HPD upper.HPD
## maladaptive 12.31 11.8 12.75
## adaptive 8.89 8.5 9.28
##
## Point estimate displayed: median
## HPD interval probability: 0.95
##
## $contrasts
## contrast estimate lower.HPD upper.HPD
## maladaptive - adaptive 3.42 2.81 4.09
##
## Point estimate displayed: median
## HPD interval probability: 0.95
BFt <- BayesFactor::ttestBF(
rw_df$is[rw_df$profile == "adaptive"],
rw_df$is[rw_df$profile == "maladaptive"],
paired = FALSE
)
effectsize(BFt)
p3 <- m3 %>%
emmeans( ~ profile) %>%
gather_emmeans_draws() %>%
ggplot(aes(x = profile, y = .value)) +
geom_eye() +
stat_summary(aes(group = NA), fun.y = mean, geom = "line") +
scale_x_discrete(labels=c('Low Resilience', 'High Resilience')) +
labs(x = "LPA Class", y = "SCS Isolation", title = "B") +
papaja::theme_apa() +
annotate("text", x = 1, y = 10.2, label = "Bayesian Cohen's d = 0.94\n 95% CI [0.79, 1.10]")
## Warning: 'geom_eye' is deprecated.
## Use 'stat_eye' instead.
## See help("Deprecated") and help("tidybayes-deprecated").
p3
m4 <- brm(
bf(oi ~ profile),
family = skew_normal(),
data = rw_df,
backend = "cmdstanr",
adapt_delta = 0.99
)
## Start sampling
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Scale parameter is 0, but must be positive! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13a5152b.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(m4)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
loo_m4 <- loo(m4)
plot(loo_m4)
summary(m4)
## Family: skew_normal
## Links: mu = identity; sigma = identity; alpha = identity
## Formula: oi ~ profile
## Data: rw_df (Number of observations: 751)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept 11.00 0.24 10.53 11.46 1.00 1602 1861
## profileadaptive -2.58 0.33 -3.23 -1.94 1.00 1255 1818
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 3.65 0.12 3.44 3.89 1.00 1334 1895
## alpha 3.41 0.86 2.07 5.50 1.00 1171 1277
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
me <- conditional_effects(
m4, "profile"
)
plot(me, points = FALSE)
emmeans(m4, specs = pairwise ~ profile)
## $emmeans
## profile emmean lower.HPD upper.HPD
## maladaptive 11.01 10.54 11.47
## adaptive 8.42 8.05 8.77
##
## Point estimate displayed: median
## HPD interval probability: 0.95
##
## $contrasts
## contrast estimate lower.HPD upper.HPD
## maladaptive - adaptive 2.58 1.93 3.21
##
## Point estimate displayed: median
## HPD interval probability: 0.95
BFt <- BayesFactor::ttestBF(
rw_df$oi[rw_df$profile == "adaptive"],
rw_df$oi[rw_df$profile == "maladaptive"],
paired = FALSE
)
effectsize(BFt)
p4 <- m4 %>%
emmeans( ~ profile) %>%
gather_emmeans_draws() %>%
ggplot(aes(x = profile, y = .value)) +
geom_eye() +
stat_summary(aes(group = NA), fun.y = mean, geom = "line") +
scale_x_discrete(labels=c('Low Resilience', 'High Resilience')) +
labs(x = "LPA Class", y = "SCS Over-Identification", title = "C") +
papaja::theme_apa() +
annotate("text", x = 1, y = 9.4, label = "Bayesian Cohen's d = 0.97\n 95% CI [0.82, 1.12]")
## Warning: 'geom_eye' is deprecated.
## Use 'stat_eye' instead.
## See help("Deprecated") and help("tidybayes-deprecated").
p4
m5 <- brm(
bf(sk ~ profile),
family = student(),
data = rw_df,
backend = "cmdstanr"
)
## Start sampling
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce137be2c7fe.stan', line 75, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce137be2c7fe.stan', line 75, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: gamma_lpdf: Random variable is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce137be2c7fe.stan', line 67, column 2 to column 66)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce137be2c7fe.stan', line 75, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce137be2c7fe.stan', line 75, column 4 to column 48)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce137be2c7fe.stan', line 75, column 4 to column 48)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce137be2c7fe.stan', line 75, column 4 to column 48)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce137be2c7fe.stan', line 75, column 4 to column 48)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce137be2c7fe.stan', line 75, column 4 to column 48)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce137be2c7fe.stan', line 75, column 4 to column 48)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: gamma_lpdf: Random variable is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce137be2c7fe.stan', line 67, column 2 to column 66)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(m5)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
loo_m5 <- loo(m5)
plot(loo_m5)
summary(m5)
## Family: student
## Links: mu = identity; sigma = identity; nu = identity
## Formula: sk ~ profile
## Data: rw_df (Number of observations: 751)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept 13.05 0.23 12.60 13.49 1.00 4519 2704
## profileadaptive 1.27 0.32 0.64 1.89 1.00 4114 2941
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 4.22 0.12 3.99 4.45 1.00 3858 3318
## nu 41.05 16.68 17.70 81.19 1.00 4210 3374
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
me <- conditional_effects(
m5, "profile"
)
plot(me, points = FALSE)
emmeans(m5, specs = pairwise ~ profile)
## $emmeans
## profile emmean lower.HPD upper.HPD
## maladaptive 13.1 12.6 13.5
## adaptive 14.3 13.9 14.7
##
## Point estimate displayed: median
## HPD interval probability: 0.95
##
## $contrasts
## contrast estimate lower.HPD upper.HPD
## maladaptive - adaptive -1.27 -1.86 -0.621
##
## Point estimate displayed: median
## HPD interval probability: 0.95
BFt <- BayesFactor::ttestBF(
rw_df$sk[rw_df$profile == "adaptive"],
rw_df$sk[rw_df$profile == "maladaptive"],
paired = FALSE
)
effectsize(BFt)
p5 <- m5 %>%
emmeans( ~ profile) %>%
gather_emmeans_draws() %>%
ggplot(aes(x = profile, y = .value)) +
geom_eye() +
stat_summary(aes(group = NA), fun.y = mean, geom = "line") +
scale_x_discrete(labels=c('Low Resilience', 'High Resilience')) +
labs(x = "LPA Class", y = "SCS Self-Kindness", title = "D") +
papaja::theme_apa() +
annotate("text", x = 1, y = 14.5, label = "Bayesian Cohen's d = 0.28\n 95% CI [0.14, 0.43]")
## Warning: 'geom_eye' is deprecated.
## Use 'stat_eye' instead.
## See help("Deprecated") and help("tidybayes-deprecated").
p5
m6 <- brm(
bf(ch ~ profile),
family = student(),
data = rw_df,
backend = "cmdstanr"
)
## Start sampling
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce131bc343a0.stan', line 75, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce131bc343a0.stan', line 75, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce131bc343a0.stan', line 75, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce131bc343a0.stan', line 75, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: gamma_lpdf: Random variable is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce131bc343a0.stan', line 67, column 2 to column 66)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: student_t_lpdf: Scale parameter is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce131bc343a0.stan', line 75, column 4 to column 48)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce131bc343a0.stan', line 75, column 4 to column 48)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: gamma_lpdf: Random variable is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce131bc343a0.stan', line 67, column 2 to column 66)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(m6)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
loo_m6 <- loo(m6)
plot(loo_m6)
summary(m6)
## Family: student
## Links: mu = identity; sigma = identity; nu = identity
## Formula: ch ~ profile
## Data: rw_df (Number of observations: 751)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept 11.60 0.18 11.25 11.95 1.00 4568 3268
## profileadaptive -0.01 0.25 -0.50 0.49 1.00 4506 2910
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 3.29 0.09 3.10 3.46 1.00 3839 3030
## nu 42.77 16.82 18.64 82.31 1.00 3643 3044
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
me <- conditional_effects(
m6, "profile"
)
plot(me, points = FALSE)
BFt <- BayesFactor::ttestBF(
rw_df$ch[rw_df$profile == "adaptive"],
rw_df$ch[rw_df$profile == "maladaptive"],
paired = FALSE
)
effectsize(BFt)
p6 <- m6 %>%
emmeans( ~ profile) %>%
gather_emmeans_draws() %>%
ggplot(aes(x = profile, y = .value)) +
geom_eye() +
stat_summary(aes(group = NA), fun.y = mean, geom = "line") +
scale_x_discrete(labels=c('Low Resilience', 'High Resilience')) +
labs(x = "LPA Class", y = "SCS Common-Humanity", title = "E") +
papaja::theme_apa() +
annotate("text", x = 1.5, y = 12.2, label = "Bayesian Cohen's d = 0.00\n 95% CI [-0.14, 0.14]")
## Warning: 'geom_eye' is deprecated.
## Use 'stat_eye' instead.
## See help("Deprecated") and help("tidybayes-deprecated").
p6
m7 <- brm(
bf(mi ~ profile),
family = student(),
data = rw_df,
backend = "cmdstanr"
)
## Start sampling
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370521460.stan', line 75, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370521460.stan', line 75, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: student_t_lpdf: Scale parameter is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370521460.stan', line 75, column 4 to column 48)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370521460.stan', line 75, column 4 to column 48)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: gamma_lpdf: Random variable is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370521460.stan', line 67, column 2 to column 66)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370521460.stan', line 75, column 4 to column 48)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370521460.stan', line 75, column 4 to column 48)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370521460.stan', line 75, column 4 to column 48)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: gamma_lpdf: Random variable is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1370521460.stan', line 67, column 2 to column 66)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(m7)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
loo_m7 <- loo(m7)
plot(loo_m7)
summary(m7)
## Family: student
## Links: mu = identity; sigma = identity; nu = identity
## Formula: mi ~ profile
## Data: rw_df (Number of observations: 751)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept 12.74 0.17 12.42 13.06 1.00 4041 3302
## profileadaptive 1.02 0.22 0.59 1.45 1.00 3551 2962
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 3.03 0.09 2.86 3.22 1.00 4043 2798
## nu 36.83 15.44 15.32 75.89 1.00 3445 3231
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
emmeans(m7, specs = pairwise ~ profile)
## $emmeans
## profile emmean lower.HPD upper.HPD
## maladaptive 12.7 12.4 13
## adaptive 13.8 13.4 14
##
## Point estimate displayed: median
## HPD interval probability: 0.95
##
## $contrasts
## contrast estimate lower.HPD upper.HPD
## maladaptive - adaptive -1.02 -1.46 -0.604
##
## Point estimate displayed: median
## HPD interval probability: 0.95
BFt <- BayesFactor::ttestBF(
rw_df$mi[rw_df$profile == "adaptive"],
rw_df$mi[rw_df$profile == "maladaptive"],
paired = FALSE
)
effectsize(BFt)
me <- conditional_effects(
m7, "profile"
)
plot(me, points = FALSE)
p7 <- m7 %>%
emmeans( ~ profile) %>%
gather_emmeans_draws() %>%
ggplot(aes(x = profile, y = .value)) +
geom_eye() +
stat_summary(aes(group = NA), fun.y = mean, geom = "line") +
scale_x_discrete(labels=c('Low Resilience', 'High Resilience')) +
labs(x = "LPA Class", y = "SCS Mindfulness", title = "F") +
papaja::theme_apa() +
annotate("text", x = 1, y = 13.8, label = "Bayesian Cohen's d = 0.32\n 95% CI [0.17, 0.46]")
## Warning: 'geom_eye' is deprecated.
## Use 'stat_eye' instead.
## See help("Deprecated") and help("tidybayes-deprecated").
p7
fig_scs <- (p2 | p3 | p4) /
(p5 | p6 | p7)
out <- fig_scs + plot_annotation(
title = 'SCS Subscales as a Function of LPA Profile'
# subtitle = 'Rescue Workers group'
# caption = 'Disclaimer: None of these plots are insightful'
)
ggsave("scs_subscales_lpa.pdf", width = 35, height = 20, units = "cm")
print(out)
m10 <- brm(
bf(ies_ts ~ class),
family = skew_normal(),
data = rw_df,
backend = "cmdstanr",
adapt_delta = 0.99
)
## Start sampling
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce136f726b53.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(m10)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
summary(m10)
## Family: skew_normal
## Links: mu = identity; sigma = identity; alpha = identity
## Formula: ies_ts ~ class
## Data: rw_df (Number of observations: 751)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept 16.79 0.67 15.41 18.06 1.00 1259 1279
## class2 4.19 0.97 2.53 6.44 1.00 1399 1353
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 13.95 0.38 13.22 14.71 1.00 1593 1704
## alpha 10.14 2.17 6.23 14.61 1.00 1453 1637
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
p10 <- m10 %>%
emmeans( ~ class) %>%
gather_emmeans_draws() %>%
ggplot(aes(x = class, y = .value)) +
geom_eye() +
stat_summary(aes(group = NA), fun.y = mean, geom = "line") +
# facet_grid(~ wool) +
# theme_light()
scale_x_discrete(labels=c('Low Resilience', 'High Resilience')) +
labs(x = "LPA Class", y = "Impact of Event Scale - Revised (IES-R)") +
# papaja::theme_apa() +
annotate("text", x = 1, y = 17, label = "Bayesian Cohen's d = 1.34\n 95% CI [1.18, 1.50]")
## Warning: 'geom_eye' is deprecated.
## Use 'stat_eye' instead.
## See help("Deprecated") and help("tidybayes-deprecated").
p10
BFt <- BayesFactor::ttestBF(
rw_df$ies_ts[rw_df$class == 1],
rw_df$ies_ts[rw_df$class == 2],
paired = FALSE
)
## t is large; approximation invoked.
effectsize(BFt)
emmeans(m10 , specs = pairwise ~ class)
## $emmeans
## class emmean lower.HPD upper.HPD
## 1 16.8 15.4 18.1
## 2 21.0 19.7 22.4
##
## Point estimate displayed: median
## HPD interval probability: 0.95
##
## $contrasts
## contrast estimate lower.HPD upper.HPD
## class1 - class2 -4.09 -6.23 -2.44
##
## Point estimate displayed: median
## HPD interval probability: 0.95
m11 <- brm(
bf(ptgi_total_score | trunc(lb = 0) ~ class),
family = student(),
data = rw_df,
backend = "cmdstanr"
)
## Start sampling
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce133e061c7c.stan', line 77, column 6 to line 78, column 60)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce133e061c7c.stan', line 77, column 6 to line 78, column 60)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: gamma_lpdf: Random variable is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce133e061c7c.stan', line 68, column 2 to column 66)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce133e061c7c.stan', line 77, column 6 to line 78, column 60)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce133e061c7c.stan', line 77, column 6 to line 78, column 60)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: student_t_lpdf: Scale parameter is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce133e061c7c.stan', line 77, column 6 to line 78, column 60)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce133e061c7c.stan', line 77, column 6 to line 78, column 60)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce133e061c7c.stan', line 77, column 6 to line 78, column 60)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: student_t_lpdf: Scale parameter is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce133e061c7c.stan', line 77, column 6 to line 78, column 60)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(m11)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
summary(m11)
## Family: student
## Links: mu = identity; sigma = identity; nu = identity
## Formula: ptgi_total_score | trunc(lb = 0) ~ class
## Data: rw_df (Number of observations: 751)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept 31.64 2.13 27.15 35.67 1.00 3239 2788
## class2 5.96 2.62 0.88 11.14 1.00 3888 2877
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 28.46 1.20 26.24 30.86 1.00 3511 2544
## nu 47.58 17.96 21.09 90.24 1.00 3562 2459
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
rw_df$job_qualification <- ifelse(
rw_df$job_qualification == "non_rescue_worker", "team_member",
rw_df$job_qualification
)
m12 <- brm(
bf(ies_ts ~ job_qualification),
family = skew_normal(),
data = rw_df,
backend = "cmdstanr",
adapt_delta = 0.99
)
## Start sampling
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: skew_normal_lpdf: Location parameter[1] is -inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13e0494e2.stan', line 49, column 4 to column 53)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(m12)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
summary(m12)
## Family: skew_normal
## Links: mu = identity; sigma = identity; alpha = identity
## Formula: ies_ts ~ job_qualification
## Data: rw_df (Number of observations: 751)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS
## Intercept 17.88 0.69 16.49 19.17 1.00 1906
## job_qualificationteam_leader 1.20 0.66 -0.05 2.57 1.00 1944
## job_qualificationteam_member 1.35 0.68 0.09 2.75 1.00 1889
## Tail_ESS
## Intercept 1806
## job_qualificationteam_leader 1537
## job_qualificationteam_member 1586
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 14.45 0.37 13.75 15.21 1.00 1942 2260
## alpha 15.57 2.21 11.51 20.10 1.00 2252 2401
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
me <- conditional_effects(
m12, "job_qualification"
)
plot(me, points = FALSE)
emmeans(m12 , specs = pairwise ~ job_qualification)
## $emmeans
## job_qualification emmean lower.HPD upper.HPD
## driver 17.9 16.5 19.2
## team_leader 19.1 18.0 20.2
## team_member 19.2 18.2 20.4
##
## Point estimate displayed: median
## HPD interval probability: 0.95
##
## $contrasts
## contrast estimate lower.HPD upper.HPD
## driver - team_leader -1.173 -2.49 0.0920
## driver - team_member -1.336 -2.68 -0.0271
## team_leader - team_member -0.159 -1.23 0.8683
##
## Point estimate displayed: median
## HPD interval probability: 0.95
m13 <- brm(
bf(scs_ts ~ job_qualification * class),
family = gaussian(),
data = rw_df,
backend = "cmdstanr",
adapt_delta = 0.99
)
## Start sampling
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce1311d85268.stan', line 35, column 4 to column 62)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(m13)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
me <- conditional_effects(
m13, "job_qualification:class"
)
plot(me, points = FALSE)
summary(m13)
## Family: gaussian
## Links: mu = identity; sigma = identity
## Formula: scs_ts ~ job_qualification * class
## Data: rw_df (Number of observations: 751)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat
## Intercept 88.98 1.54 86.00 92.07 1.01
## job_qualificationteam_leader -1.23 1.96 -5.00 2.67 1.00
## job_qualificationteam_member -2.88 1.95 -6.66 0.87 1.00
## class2 -9.86 2.52 -14.72 -4.96 1.00
## job_qualificationteam_leader:class2 -3.12 3.05 -9.03 2.70 1.00
## job_qualificationteam_member:class2 -4.32 3.13 -10.40 1.81 1.00
## Bulk_ESS Tail_ESS
## Intercept 1592 2471
## job_qualificationteam_leader 1662 2029
## job_qualificationteam_member 1683 2342
## class2 1480 1921
## job_qualificationteam_leader:class2 1501 1786
## job_qualificationteam_member:class2 1506 1803
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 14.80 0.38 14.08 15.56 1.00 3453 2817
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
emmeans(m13 , specs = pairwise ~ job_qualification*class)
## $emmeans
## job_qualification class emmean lower.HPD upper.HPD
## driver 1 89.0 86.1 92.1
## team_leader 1 87.7 85.5 90.1
## team_member 1 86.1 83.9 88.4
## driver 2 79.2 75.1 82.7
## team_leader 2 74.8 72.3 77.3
## team_member 2 71.9 69.6 74.4
##
## Point estimate displayed: median
## HPD interval probability: 0.95
##
## $contrasts
## contrast estimate lower.HPD upper.HPD
## driver class1 - team_leader class1 1.26 -2.636 5.02
## driver class1 - team_member class1 2.89 -0.877 6.66
## driver class1 - driver class2 9.82 5.313 14.98
## driver class1 - team_leader class2 14.24 9.987 17.89
## driver class1 - team_member class2 17.05 13.009 20.86
## team_leader class1 - team_member class1 1.61 -1.531 4.93
## team_leader class1 - driver class2 8.58 4.149 13.14
## team_leader class1 - team_leader class2 12.97 9.620 16.38
## team_leader class1 - team_member class2 15.81 12.633 19.22
## team_member class1 - driver class2 6.97 2.663 11.24
## team_member class1 - team_leader class2 11.33 7.909 14.75
## team_member class1 - team_member class2 14.16 10.760 17.63
## driver class2 - team_leader class2 4.33 -0.134 8.92
## driver class2 - team_member class2 7.24 2.704 11.78
## team_leader class2 - team_member class2 2.83 -0.533 6.47
##
## Point estimate displayed: median
## HPD interval probability: 0.95
mydf <- data.frame(
scs = scale(rw_df$scs_ts),
class = ifelse(rw_df$class == 1, 0.0, 1.0),
ptgi = scale(rw_df$ptgi_total_score),
psc = scale(rw_df$sk + rw_df$ch + rw_df$mi),
nsc = scale(rw_df$sj + rw_df$oi + rw_df$is),
commettee = rw_df$red_cross_commeetee_location,
id = 1:nrow(rw_df)
)
mydf <- mydf[complete.cases(mydf), ]
rw_df$rate_of_activity_num <- as.integer(rw_df$rate_of_activity_num)
temp <- rw_df[1:746, ]
temp$activity <- cut(
temp$rate_of_activity_num,
breaks = c(-1, 0, 1, 2),
labels = c("Low", "Medium", "High"),
include.lowest = TRUE,
ordered_result = TRUE
)
m19 <- brm(
bf(activity ~ class),
family=cumulative("logit"),
data = temp,
backend = "cmdstanr",
adapt_delta = 0.99
)
## Start sampling
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: ordered_logistic: Cut-points is not a valid ordered vector. The element at 2 is -83.0512, but should be greater than the previous element, -83.0512 (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13670dc662.stan', line 84, column 6 to column 63)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: ordered_logistic: Cut-points is not a valid ordered vector. The element at 2 is -83.2996, but should be greater than the previous element, -83.2996 (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13670dc662.stan', line 84, column 6 to column 63)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: ordered_logistic: Cut-points is not a valid ordered vector. The element at 2 is -20.3539, but should be greater than the previous element, -20.3539 (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13670dc662.stan', line 84, column 6 to column 63)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: ordered_logistic: Final cut-point is inf, but must be finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13670dc662.stan', line 84, column 6 to column 63)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: ordered_logistic: Cut-points is not a valid ordered vector. The element at 2 is 1195.91, but should be greater than the previous element, 1195.91 (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13670dc662.stan', line 84, column 6 to column 63)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: ordered_logistic: Cut-points is not a valid ordered vector. The element at 2 is -13719.4, but should be greater than the previous element, -13719.4 (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13670dc662.stan', line 84, column 6 to column 63)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: ordered_logistic: Cut-points is not a valid ordered vector. The element at 2 is -130.227, but should be greater than the previous element, -130.227 (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13670dc662.stan', line 84, column 6 to column 63)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: ordered_logistic: Cut-points is not a valid ordered vector. The element at 2 is -803.409, but should be greater than the previous element, -803.409 (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13670dc662.stan', line 84, column 6 to column 63)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(m19)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
summary(m19)
## Family: cumulative
## Links: mu = logit; disc = identity
## Formula: activity ~ class
## Data: temp (Number of observations: 746)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept[1] -0.41 0.10 -0.61 -0.22 1.00 2514 2257
## Intercept[2] 1.48 0.11 1.26 1.71 1.00 3608 2561
## class2 -0.03 0.14 -0.30 0.24 1.00 2940 2747
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## disc 1.00 0.00 1.00 1.00 NA NA NA
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
conditional_effects(m19, "class")
## Warning: Predictions are treated as continuous variables in
## 'conditional_effects' by default which is likely invalid for ordinal families.
## Please set 'categorical' to TRUE.
m20 <- brm(
bf(class ~ last_training_num * scs_ts),
family=bernoulli(),
data = temp,
backend = "cmdstanr",
adapt_delta = 0.99
)
## Start sampling
summary(m20)
## Family: bernoulli
## Links: mu = logit
## Formula: class ~ last_training_num * scs_ts
## Data: temp (Number of observations: 746)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS
## Intercept 4.01 0.87 2.29 5.74 1.00 1153
## last_training_num 0.09 0.09 -0.07 0.27 1.00 1150
## scs_ts -0.05 0.01 -0.07 -0.03 1.00 1142
## last_training_num:scs_ts -0.00 0.00 -0.00 0.00 1.00 1159
## Tail_ESS
## Intercept 1466
## last_training_num 1165
## scs_ts 1428
## last_training_num:scs_ts 1253
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
conditional_effects(m20, "scs_ts:last_training_num")
table(rw_df$class, rw_df$last_training_num)
##
## 1 3 4 8 10 18
## 1 83 21 77 12 130 85
## 2 67 9 48 19 121 74
hist(temp$last_training_num)
m21 <- brm(
bf(last_training_num ~ class),
family=gaussian(),
data = temp,
backend = "cmdstanr",
adapt_delta = 0.90
)
## Start sampling
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 1 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 1 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 1 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 1 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 1
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 2 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 2
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 3 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 3 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 3 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 3 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 3
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: normal_id_glm_lpdf: Scale vector is inf, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
## Chain 4 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
## Chain 4 Exception: normal_id_glm_lpdf: Scale vector is 0, but must be positive finite! (in '/var/folders/cy/4xdvhqx966nggmk95hsnyzc40000gn/T/RtmpFWxTAx/model-ce13545b87.stan', line 35, column 4 to column 62)
## Chain 4 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
## Chain 4 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
## Chain 4
pp_check(m21)
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
summary(m21)
## Family: gaussian
## Links: mu = identity; sigma = identity
## Formula: last_training_num ~ class
## Data: temp (Number of observations: 746)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept 8.29 0.30 7.72 8.88 1.00 3922 2963
## class2 0.53 0.43 -0.31 1.34 1.00 3872 2509
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 6.01 0.16 5.72 6.32 1.00 3876 2658
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).